Outlier Protection in Continuous Microdata Masking

Masking methods protect data sets against disclosure by perturbing the original values before publication. Masking causes some information loss (masked data are not exactly the same as original data) and does not completely suppress the risk of disclosure for the individuals behind the data set. Information loss can be measured by observing the di#erences between original and masked data while disclosure risk can be measured by means of record linkage and confidentiality intervals